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The wide application of sensor networks has brought great challenges to cloud data storage, such as transmission security, data privacy protection and financial risk control. In order to deal with these challenges, the system establishes a comprehensive management early warning system to ensure the data security and financial risk control of the sensor network. The system integrates sensor network technology and cloud data storage technology, and stores data in the cloud through the collection and transmission of environmental data by sensor nodes. In order to ensure the security of the stored process, the system adopts a series of security mechanisms, such as data encryption, access control and identity authentication, and also introduces the financial risk control module, which helps users to warn and manage financial risks through real-time monitoring and analysis of data in the sensor network. The system provides a user-friendly management interface, allowing users to easily configure and monitor the operating state of the sensor network, and supports flexible expansion and customization to adapt to the needs of different scenarios. Through the application of this system, users can effectively manage and control the security and financial risks of sensor networks in cloud data storage, and improve the efficiency and reliability of data storage management.

In the Internet of Things (IoT) era, the surge in Machine-Type Devices (MTDs) has introduced Massive IoT (MIoT), opening new horizons in the world of connected devices. However, such proliferation presents challenges, especially in storing and analyzing massive, heterogeneous data streams in real time. In order to manage Massive IoT data streams, we utilize analytical database software such as Apache Druid version 28.0.0 that excels in real-time data processing. Our approach relies on a publish/subscribe mechanism, where device-generated data are relayed to a dedicated broker, effectively functioning as a separate server. This broker enables any application to subscribe to the dataset, promoting a dynamic and responsive data ecosystem. At the core of our data transmission infrastructure lies Apache Kafka version 3.6.1, renowned for its exceptional data flow management performance. Kafka efficiently bridges the gap between MIoT sensors and brokers, enabling parallel clusters of brokers that lead to more scalability. In our pursuit of uninterrupted connectivity, we incorporate a fail-safe mechanism with two Software-Defined Radios (SDR) called Nutaq PicoLTE Release 1.5 within our model. This strategic redundancy enhances data transmission availability, safeguarding against connectivity disruptions. Furthermore, to enhance the data repository security, we utilize blockchain technology, specifically Hyperledger Fabric, known for its high-performance attributes, ensuring data integrity, immutability, and security. Our latency results demonstrate that our platform effectively reduces latency for 100,000 devices, qualifying as an MIoT, to less than 25 milliseconds. Furthermore, our findings on blockchain performance underscore our model as a secure platform, achieving over 800 Transactions Per Second in a dataset comprising 14,000 transactions, thereby demonstrating its high efficiency. [ABSTRACT FROM AUTHOR]

Cloud computing refers to the management of data and servers and the provision of technology services using cloud computing technology. It is commonly used to store large amounts of data on cloud platforms. As a result, it is essential to safeguard data in various formats such as text, audio, video, and others. This paper presents a research study on cloud security, focusing on AWS, the most trusted cloud computing provider. AWS offers not only cloud security but also cloud storage services. The document addresses several key security challenges, including virtualization security, data storage in the cloud, and risk tolerance assessment in cloud computing. As the cloud grows, it is increasingly important to understand and implement effective security measures to protect sensitive information and maintain trust in cloud-based services. [ABSTRACT FROM AUTHOR]

The pervasive proliferation of embedded, mobile, and IoT devices continue to change our lifestyle dramatically. However, the huge increase in these devices has come with critical breaches to data resting inside them. Many types of such data are considered to be sensitive and confidential. Because the most sensitive data of such devices are resting in databases, focusing on encrypting SQLite databases will be more efficient than full disk encryption (FDE). While SQLite is a very popular, lightweight, and easy-to-use relational database suitable for embedded and mobile devices, its stored data suffers serious security risks. If an attacker can gain access to higher system privileges or find a way to access the database plain file, he can tamper with the database files and user-sensitive data, which breaches the security CIA triad of SQLite. To ensure data confidentiality in SQLite databases of embedded devices, we present a design and implementation of a parallel database encryption system, called SQLite-XTS. The developed system encrypts the database pages on- the-fly in a transparent manner without user intervention. Because performance is a critical issue, SQLite-XTS utilizes multi-core processors coming with most current mobile and embedded devices. The developed parallel SQLite-XTS was successfully implemented and integrated into a testbed device. To assess the performance and feasibility of this system, it was compared to three other SQLite implementations: plain SQLite, serial XTS SQLite, and SQLCipher-CBC. The results show that SQLite-XTS reduces the overhead of database encryption from 30.8% with serial implementation to 17.8% when SQLite-XTS is used. This provides the developed system with an efficiency of 73% compared with its serial counterpart. The results clarify that SQLite-XTS introduces significant performance improvements compared to other implementations. Experiments also show that the system has a very low impact on the memory of these resource-limited devices.

In Hybrid Cloud Security, we combine symmetric encryption with key management to ensure anonymity. Our method provides a flexible and scalable deployment solution for cloud-based data security. To store, analyse, and deal with data, cloud computing relies on a core concept: sharing resources. Since cloud services are utilized by many individuals and are dispersed across the Internet, they provide a number of security vulnerabilities. Due to their worldwide accessibility, hybrid clouds open up a wide range of opportunities. The security solution works with a wide variety of PaaS, SaaS, and even IaaS cloud services (Infrastructure as a Service). It also works with most Cloud services out there. Hybrid public key cryptosystems can improve cloud security. Businesses are wary about cloud computing due to security concerns. The primary goal of this research is to strengthen the security of cloud computing by fusing the cryptographic models of Rabin and Rivest-Shamir-Adleman (RSA). Evaluating the efficacy of a hybrid approach to producing secret keys for data encryption and decryption. The purely RSA-based system has higher latency and is less computationally intensive than the hybrid system. [ABSTRACT FROM AUTHOR]

Information storage and access in multi-cloud environments have become quite prevalent. In this paper, a multi-cloud framework is presented that secures users' data. The primary goal of this framework is to secure users' data from untrusted Cloud Service Providers (CSPs). They can collude with other malicious users and can hand over users' data to these malicious users for their beneficial interests. In order to achieve this goal, the data are split into parts, and then each part is encrypted and uploaded to a different cloud. Therefore, client-side cryptography is used in this framework. For encrypting users' data, the BDNA encryption technique is used. This framework presents a hybrid cryptographic approach that uses Identity-based Broadcast Encryption (IBBE) for managing the keys of the symmetric key algorithm (BDNA) by encrypting them with the particular version of IBBE. The work presented in this research paper is the first practical implementation of IBBE for securing encryption keys. Earlier, IBBE was only used for securely broadcasting data across many users over a network. The security of this hybrid scheme was proved through Indistinguishable Chosen-Ciphertext Attacks. This double encryption process makes the framework secure against all insiders and malicious users' attacks. The proposed framework was implemented as a web application, and real-time storage clouds were used for storing the data. The workflow of the proposed framework is presented through screenshots of different working modules. [ABSTRACT FROM AUTHOR]

Summary: CO2 geological storage (CGS) is one of the important means to effectively reduce greenhouse gas emissions. Mineral trapping is an important factor affecting long‐term storage security. The process of mineral trapping is significantly affected by mineral reaction kinetics. Therefore, it is of great significance to clarify the influence trend and degree of the control equation of mineral reaction kinetics on predicting the process of CO2 storage and the amount of mineral sequestration. In this paper, the effect of different reaction rate equations on predicting long‐term CO2 sequestration mechanisms are compared and analyzed by numerical simulation using the existing reaction rate equations. The results show that different reaction rate equations of related minerals have no significant effect on predicting the total amount of CO2 sequestration and the transformation relationship among different minerals, but will significantly affect different forms of CO2 sequestration, especially mineral trapping. The ratio of mineral trapping predicted by different reaction rate equations is 20% to 41%. And the predicted CO2 mineral trapping rate is twice as high when the linear rate equation is used as when the nonlinear rate equation is used. In previous studies, linear rate equations have been widely used to describe the dissolution/precipitation reactions of related minerals, which may greatly overestimate the reaction rate and theoretical capture capacity of minerals. Therefore, it is urgent to carry out reaction kinetics experiments and numerical simulation studies on various major minerals under the condition of CO2 geological storage in the future, to obtain a more accurate mineral dissolution/precipitation reaction rate equation and improve the ability to evaluate the long‐term CO2 geological sequestration safety. [ABSTRACT FROM AUTHOR]

Ransomware is a growing concern in business and government because it causes immediate financial damages or loss of important data. There is a way to detect and block ransomware in advance, but evolved ransomware can still attack while avoiding detection. Another alternative is to back up the original data. However, existing backup solutions can be under the control of ransomware and backup copies can be destroyed by ransomware. Moreover, backup methods incur storage and performance overhead. In this article, we propose AMOEBA, a device-level backup solution that does not require additional storage for backup. AMOEBA is armed with: 1) a hardware accelerator to run content-based detection algorithms for ransomware detection at high speed and 2) a fine-grained backup control mechanism to minimize space overhead for data backup. For evaluations, we not only implemented AMOEBA using the Microsoft solid-state drive (SSD) simulator but also prototyped it on the OpenSSD-platform. Our extensive evaluations with real ransomware workloads show that AMOEBA has high ransomware detection accuracy with negligible performance overhead. [ABSTRACT FROM AUTHOR]

Cloud storage service has shown its great power and wide popularity which provides fundamental support for rapid development of cloud computing. However, due to management negligence and malicious attack, there still lie enormous security incidents that lead to quantities of sensitive data leakage at cloud storage layer. From the perspective of protecting cloud data confidentiality, this paper proposed a Cloud Secure Storage Mechanism named CSSM. To avoid data breach at the storage layer, CSSM integrated data dispersion and distributed storage to realize encrypted, chucked and distributed storage. In addition, CSSM adopted a hierarchical management approach and combined user password with secret sharing to prevent cryptographic materials leakage. The experimental results indicate that proposed mechanism is not only suitable for ensuring the data security at storage layer from leakage, but also can store huge amount of cloud data effectively without imposing too much time overhead. For example, when users upload/download 5G sized file with CSSM, it only takes 646seconds/269seconds, which is acceptable for users.

• Classification and analysis of geological heterogeneous factors for accurate simulations. • Quantification assessment of CO 2 storage parameters using two sensitivity methods. • Various heterogeneous factors exert distinct influences on CO 2 plume and BHP in different layers and time. • A method to enhance CO 2 storage modeling precision with limited data. The intensifying global climate change has prompted the imperative implementation of CO 2 capture and storage (CCS) projects as a mitigation strategy. Ensuring the safety and reliability of these projects requires meticulous validation, including the establishment of geological models and conducting numerical simulations. In CO 2 geological storage initiatives, the limitation of well data during the initial stages leads to data deficiency. This scarcity compromises the precision of geological and numerical models, hindering their ability to accurately depict actual subsurface conditions. Meanwhile, parameters related to heterogeneity significantly also impact storage effectiveness and safety. This study addresses these challenges by utilizing the Shenhua CCS demonstration project as a case study. Various heterogeneous parameters are selected, and local and global sensitivity analysis methods are subsequently introduced to determine the ranges and sequences of these parameters in numerical simulations. The simulation results can aid in assessing the influence of various heterogeneous parameters on the CO 2 plume and bottom hole pressure. The study establishes the importance ranking of various heterogeneous parameters under different temporal and spatial conditions through sensitivity analysis. The findings reveal the following key points: 1. During the small-scale injection period, the CO 2 plume is particularly sensitive to variations in net-to-gross and vertical permeable properties. 2. During and after larger-scale injections, the net-to-gross significantly impacts plume evolution, while bottom hole pressure is predominantly influenced by variations in vertical permeable properties. 3. Both the CO 2 plume and well bottom pressure are primarily affected by changes in sand body morphologies, especially at low net-to-gross scenarios. These conclusions assist in prioritizing the collection of critical parameter data in CCS projects, facilitating the establishment of more precise and reliable geological and numerical simulation models. The heightened accuracy and reliability of these models contribute to improving their predictive capabilities, ultimately guiding engineering practices. [ABSTRACT FROM AUTHOR]

Combining the practical engineering problems of CO2 geological storage and utilization with intelligent optimization technology can maximize CO2 utilization rate, oil and gas reservoir recovery and economic benefits. The suitable storage sites for CO2 geological storage, the potential of CO2 geological storage for oil and gas reservoirs and the main storage projects are introduced. The research status of intelligent optimization technology in joint optimization of recovery and storage stock is reviewed. The advantages and disadvantages of different intelligent optimization technologies are compared. Combined with the application of well location optimization, injection and production optimization and surrogate model optimization technology in mitigating leakage risk, the intelligent optimization technology suitable for CO2 geological storage and utilization is obtained, and the future development trends are put forward. [ABSTRACT FROM AUTHOR]

• A suite of 3D models with faulting and variable reservoir dip were built based on the Shenhua CCS demonstration site. • Plume migration and volumetric storage were found to be a function of reservoir dip and high transmissibility fault zone. • The results will help to inform site selection for future CCS projects in the Ordos Basin and other potential storage sites. Carbon dioxide (CO 2) storage security is a key issue in CO 2 geological storage (CGS). A three-dimensional (3D) conceptual reservoir model of the Shenhua CO 2 geological storage site in the Ordos Basin has been used to investigate the impact of reservoir formation dip and the influence of enhanced permeability fault zones on CO 2 storage and migration security. A total of 8 simulations were carried out using the TOUGH2 integral finite difference modelling code with the ECO2N fluid property module. The simulation results showed that the dip of the reservoir formation and fault had a significant impact on CO 2 migration and storage security. Increasing the dip of the reservoir increased CO 2 migration distance, decreased the total volume of CO 2 safely stored in the formation and resulted in increased maximum gas saturation and liquid mass fraction of dissolved CO 2. The presence of fault provided a channel for CO 2 leakage and caused an irregular distribution of formation pressure. The onset time of leakage through the fault proved to be a function of formation dip, occurring at 465, 230, and 160 years following commencement of CO 2 injection for dips of 5°, 10°, and 15° respectively. The lateral extent of both the high saturation CO 2 plume and the plume of dissolved CO 2 was greater in the steeply dipping faulted reservoir model, suggesting that gently dipping un-faulted reservoir formations should be selected for future CGS projects in the Ordos Basin. [ABSTRACT FROM AUTHOR]

Secure storage devices are a good example of the Internet of Things (IoTs), which require secure access control mechanisms via using the prominent pubic key cryptographic systems, e.g. RSA, ECC and related systems. However, quantum computer is in a position to attack RSA, ECC and other signature algorithms adopted by many storage devices. Therefore, storage security is facing severe threats. In this paper, an efficient hardware architecture based on multivariate scheme for storage devices is proposed. Multivariate scheme belongs to multivariate public key cryptography (MPKC), which uses affine transformations and central map transformations during cryptographic operations. The advantage of adopting multivariate scheme is that multivariate scheme is immune to quantum computer attack. The efficient hardware architecture is composed of processor module, cryptographic module, storage module, display module, power module, keyboard module, export module and terminal module (off-chip). We implement the hardware architecture on the methodology of TSMC-0.18 μm standard cell CMOS Application Specific Integrated Circuit. The implementation results show that the architecture based on multivariate scheme is very efficient and well suit for storage devices. [ABSTRACT FROM AUTHOR]

In cloud computing, data owners host their data on cloud servers, and users (data consumers) can access the data from the cloud servers. This new paradigm of data hosting service also introduces new security challenges that require an independent auditing service to check the integrity of the data in the cloud. Some existing methods for checking the integrity of the data cannot handle this problem efficiently and they cannot deal with the error condition. Thus, a secure and efficient dynamic auditing protocol should reject requests that are made with improper authentication. In addition, an excellent remote data authentication method should be able to collect information for statistical analysis, such as validation results. In this paper, first we design an auditing framework for cloud storage systems and propose an efficient and privacy-preserving auditing protocol. Then, we extend our auditing protocol to support dynamic data operations, which is efficient and has been proven to be secure in the random oracle model. We extended our auditing protocol further to support bidirectional authentication and statistical analysis. In addition, we use a better load distribution strategy, which greatly reduces the computational overhead of the client. Last, we provide an error response scheme, and our experiments show that our solution has good error-handling ability and offers lower overhead expenses for computation and communication than other approaches.

In the last one and a half decade there has been a lot of activity toward development of cryptographic techniques for disk encryption. It has been almost canonized that an encryption scheme suitable for the application of disk encryption must be length preserving, i.e., it rules out the use of schemes such as authenticated encryption where an authentication tag is also produced as a part of the ciphertext resulting in ciphertexts being longer than the corresponding plaintexts. The notion of a tweakable enciphering scheme (TES) has been formalized as the appropriate primitive for disk encryption, and it has been argued that they provide the maximum security possible for a tagless scheme. On the other hand, TESs are less efficient than some existing authenticated encryption schemes. Also TES cannot provide true authentication as they do not have authentication tags. In this paper, we analyze the possibility of the use of encryption schemes where length expansion is produced for the purpose of disk encryption. On the negative side, we argue that nonce-based authenticated encryption schemes are not appropriate for this application. On the positive side, we demonstrate that deterministic authenticated encryption (DAE) schemes may have more advantages than disadvantages compared to a TES when used for disk encryption. Finally, we propose a new deterministic authenticated encryption scheme called BCTR which is suitable for this purpose. We provide the full specification of BCTR, prove its security and also report an efficient implementation in reconfigurable hardware. Our experiments suggests that BCTR performs significantly better than existing TESs and existing DAE schemes. [ABSTRACT FROM AUTHOR]

Storing CO 2 for geological timescales is crucial to delivering decarbonisation of industrial economies aligned with global climate change mitigation objectives. This requires CO 2 injection into a large subsurface pore space overlain by a high capillary entry pressure seal rock to prevent CO 2 escape. Such formations occur abundantly in productive hydrocarbon basins such as the North Sea. However, these geological conditions for CO 2 storage are unavailable close to some large CO 2 emitting economic areas in China. We identify this problem and innovate a solution for the example of the Pearl River Mouth Basin (China). This offshore basin has an estimated effective storage capacity of hundreds of Gt CO 2 based on reservoir pore volumes. Production and geological data of three oil fields of the Huizhou hydrocarbon cluster are analysed as analogues for large-scale aquifer storage of CO 2 . Results suggest the injection and storage of CO 2 in individual trap structures will perform poorly, due to thin reservoir layers, small structural traps, and indications that the cap rocks may have only limited sealing capability. To address this a novel alternative CO 2 sequestration strategy, based on multi reservoir layer injection and dispersion trapping, is recommended to exploit the vast available pore space for CO 2 storage. [ABSTRACT FROM AUTHOR]

• Composite confining systems are multi-layer systems of discontinuous barriers. • They work by drastically lowering effective Kv/Kh, creating long flow paths for CO 2. • Migration-assisted trapping effectively immobilizes CO 2 with little vertical migration. • Risks are familiar—legacy wells, permeable faults and high-relief structures. • Composite confining systems are ideally suited to the goal of permanent sequestration. Permanent containment is paramount for geologic carbon sequestration. Petroleum experience proves the possibility but also creates bias—to date, carbon storage projects have used seals similar to those of producing petroleum accumulations—thick, laterally extensive, effectively impermeable layers. These work for CO 2 , but may not be present where needed, nor optimal for sequestration. We introduce the concept of composite confining systems, defined here as multi-layer stratigraphic systems of discontinuous barriers with no a priori requirements for continuity or minimum capillary entry pressure. We explore the concept through physical analog modeling, geologic characterization and full-scale numerical modeling. We find that barriers need only offer enough capillary entry pressure contrast to divert the flow of CO 2 and that barrier frequency and barrier area are the key variables in retarding vertical migration. Data from Southern Louisiana Miocene deltaic deposits shows ∼5–15 mudstone barriers/100 m of section, with average mudstone lengths of over 1 km and aspect ratios ∼2:1, giving effective ratios of vertical to horizontal permeability (k v /k h) of ∼0.0005. Full-scale reservoir models show that these systems can completely arrest vertical migration of industrial-scale volumes of CO 2 (10's of megatons) within a few 10's of meters of stratigraphic section. Unlike more conventional petroleum seals and traps, which retain CO 2 in a concentrated, mobile state, composite confining systems disperse and immobilize it via migration-assisted trapping. The greatest risks to performance of composite confining systems are the same as for conventional seals–the potential shortcuts across stratigraphic barriers, e.g., legacy wells, fluid escape pipes and permeable faults that focus flow. [ABSTRACT FROM AUTHOR]

In this work, we investigate the pressure-limited storage capacity of the Utsira formation. We employ the use of a simple capacity estimate based on maximum sustainable pressure. Here, the pressure during injection or post-injection cannot exceed the least compressive stress at the base of the caprock at any location. Given the global capacity estimate, large-scale simulations are performed to determine if the global capacity can be reasonably attained given local injectivity constraints and long-term CO 2 trapping. We find that the Utsira can withstand injection rates over 100 Mt/y for 50 years, which is equivalent to 8.3 Gt of CO 2 . [ABSTRACT FROM AUTHOR]

The huge proliferation of mobile and handheld devices, such as tablets and Smartphone devices, has come with different threats to the sensitive data and personally identifiable information stored inside these devices. The most efficient way to ensure data protection is through encryption; however, it comes with great impact on these small gadgets, which suffer from limited resources. Majority of recent mobile devices are equipped with increasingly powerful multi-core processors that researchers can leverage in order to enhance data protection while maintaining proper device performance. In this paper, we introduce a parallel implementation for data encryption inside the storage of Android-based mobile devices. This work implements a multi-core design of different encryption ciphers, making use of the commodity multi-core CPUs available currently in new smart gadget devices, in order to enhance the performance inside these resource-limited devices. Ciphers XTS-AES, XTS-Twofish, and XTS-RC6 are used during the experiments; however, the main focus is given to XTS-AES because it is developed specifically for storage encryption. Parallel encryption experiments are conducted on a mobile device, and performance comparisons are presented. The parallel XTS-AES has shown a maximum performance speedup of 1.71, with 86% efficiency, faster than the serial counterpart, with higher encryption throughput in the device up to 8290 and 11 380 KB/s when using XTS-AES and XTS-RC6 ciphers, respectively. In addition, we performed comparison between mobile device and desktop machine using similar experimental setup. It shows that the performance of storage encryption in mobile devices still lags by more than 10 folds when compared with desktop environment. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Storage strata are usually generalized as horizontal when using numerical simulation methods to analyze CO2 geological storage in saline aquifers. However, horizontal strata are not common in nature. Most strata have gradients, because of the effects of geological structure and diagenesis. Based on the actual strata dip angle variation range of two CO2 injection demonstration projects in China, five modeling schemes were designed to investigate the impact of formation dip on CO2 storage amount and space migration of gas-phase CO2 in reservoir formation. The results show that the total CO2 storage amount is inversely proportional to formation dip, and after injection is halted, storage amounts of upper and lower parts of the same stratum reservoir have a reverse trend. Formation dip has a significant impact on the migration of CO2. The greater the formation dip, the more significant the effect on CO2 migration distance. Given the low porosity and permeability of the Shiqianfeng formation reservoir in the case study, when the stratum dip angle is 16°, at centennial time scale, CO2 migration distance is 47.06% greater than that in the horizontal reservoir. We expect that for storage reservoirs with high porosity and permeability, the influence of formation dip on CO2 migration will be more significant. Because non-horizontal strata are predominant in deep saline aquifers in nature, regardless of the influence of formation dip, CO2 leakage risks in geological storage will be greatly underestimated. Therefore, in research related to CO2 geological storage, the stratum dip angle must be considered. © 2016 Society of Chemical Industry and John Wiley & Sons, Ltd [ABSTRACT FROM AUTHOR]

Comprehensive security mechanisms are required for a successful implementation of the Internet of Things (IoT). Existing solutions focus mainly on securing the communication links between Internet hosts and IoT devices. However, as most IoT devices nowadays provide vast amounts of flash storage space, it is as well required to consider storage security within a comprehensive security framework. Instead of developing independent security solutions for storage and communication, we propose Fusion, a framework that provides coalesced confidential storage and communication. Fusion uses existing secure communication protocols for the IoT such as Internet protocol security (IPsec) and datagram transport layer security (DTLS) and re-uses the defined communication security mechanisms within the storage component. Thus, trusted mechanisms developed for communication security are extended into the storage space. Notably, this mechanism allows us to transmit requested data directly from the file system without decrypting read data blocks and then re-encrypting these for transmission. Thus, Fusion provides benefits in terms of processing speed and energy efficiency, which are important aspects for resource-constrained IoT devices. This paper describes the Fusion architecture and its instantiation for IPsec-based and DTLS-based systems. We describe Fusion's implementation and evaluate its storage overheads, communication performance, and energy consumption. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

As secure storage becomes more pervasive throughout the enterprise,the focus quickly moves from implementing encrypting storage devices toestablishing effective and secure key management policies. Without the properkey generation, distribution, storage, and recovery, valuable data will beeventually compromised [9]. Although a considerable amount of research hasbeen dedicated to encryption algorithms in the past decades, key managementbecomes an issue due to the quantity of data. For example, with millions of datayou will need million set of keys. To manage and keep track of these keys,complexity and operational inefficiency becomes an issue. How to manage keysbecomes a challenging task. Adequate understanding of these new challenges isessential to effectively devise new key management policies and mechanisms toguard against them. We discuss many of these methods in this new context tofill this gap